Detecting Arbitrarily Oriented Text Labels in Early Maps

In this work, we propose a novel method for robust, scale and rotation independent text/graphics separation for early maps. We apply a connected component analysis with density, minimum and maximum diameter as main features. In addition, we use a combined threshold region for the density and the ratio of maximum and minimum diameter, extended by an analysis of neighboring components to recognize text with large variations in style, size and orientations. Our method reaches an F1-score of 0.73 which is 0.19 higher than the 0.54 achieved by a state-of-the-art approach from the literature on the same test data set.

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